Skin Cancer Detection using TensorFlow in Python. Using deep learning and neural networks, we'll be able to classify benign and malignant skin diseases. We will make a skin disease classifier that tries to distinguish between benign (nevus and seborrheic keratosis) and malignant (melanoma) skin diseases from only photographic images using TensorFlow framework in Python.
Learn how to use transfer learning to build a model that is able to classify benign and malignant (melanoma) skin diseases in Python using TensorFlow 2.
Skin cancer is an abnormal growth of skin cells, it is one of the most common cancers and unfortunately, it can become deadly. The good news though, is when caught early, your dermatologist can treat it and eliminate it entirely.
Using deep learning and neural networks, we'll be able to classify benign and malignant skin diseases, which may help the doctor diagnose the cancer in an earlier stage. In this tutorial, we will make a skin disease classifier that tries to distinguish between benign (nevus and seborrheic keratosis) and malignant (melanoma) skin diseases from only photographic images using TensorFlow framework in Python.
This video explains four reasons why deep learning has become so popular in past few years. In this deep learning tutorial python, I will cover following things in this video: Introduction; Data growth; Hardware advancements; Python and opensource ecosystem; Cloud and AI boom
In this video I am discussing various techniques to handle imbalanced dataset in machine learning. I also have a python code that demonstrates these different techniques. In the end there is an exercise for you to solve along with a solution link. Credit card fraud detection, cancer prediction, customer churn prediction are some of the examples where you might get an imbalanced dataset. Training a model on imbalanced dataset requires making certain adjustments otherwise the model will not perform as per your expectations.
Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial: How to use Keras, a neural network API written in Python and integrated with TensorFlow. We will learn how to prepare and process data for artificial neural networks, build and train artificial neural networks from scratch, build and train convolutional neural networks (CNNs), implement fine-tuning and transfer learning, and more!
In this article, we will learn how deep learning works and get familiar with its terminology — such as backpropagation and batch size
Deep Learning with Python tutorial will help you understand what is deep learning, applications of deep learning, what is a neural network, biological versus artificial neural networks, activation functions, cost function, how neural networks work, and what gradient descent is. Finally, we'll code a neural network in Python using TensorFlow.